Cloud Computing Concepts, Part 1

Cloud Computing Concepts, Part 1

University of Illinois at Urbana-Champaign

About this course: Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing.
Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more!
Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises. In the programming assignments, implement some of these concepts in template code (programs) provided in the C++ programming language. Prior experience with C++ is required.
The course also features interviews with leading researchers and managers, from both industry and academia.

Who is this class for: Who this class is for: This course is intended for students with similar backgrounds as junior or senior undergraduates in computer science. This course will teach you basic algorithmic and design concepts for distributed systems, as used in today’s cloud systems. Much of the course, including quizzes, is conceptual and not programming oriented. The programming assignment assumes some knowledge of C++ (if you have only Java experience, you should be able to pick up C++ quickly may suffice), and allow you to write distributed algorithms in an emulated distributed system on your own machine. To ensure you have the necessary prerequisites, you need to take the prerequisite quiz and achieve a high passing score (at least 90%, preferably 100%). Based on prior student experiences, the Linux/Unix environment may work better for the programming assignments than Windows.
Who this class is NOT for: This course is NOT intended for those: (1) wishing to get a high level overview of cloud computing (you can use Wikipedia for that); (2) wishing to do detailed programming in a real cloud (the Cloud Capstone and Cloud Applications MOOCs provide you that); (3) who are averse to theoretical and algorithmic concepts; (4) with little or no prior programming experience in C++ or Java; (5) who expect to see industry-quality code in programming assignments (these are play programming assignments focused on allowing you to implement concepts you learn from lectures, and are not intended for immediate deployment); (6) those not familiar with setting up IDEs/compilers, etc., especially for C++; or (7) those who want to rush through lectures and/or videos and attempt quizzes in haste (quizzes are hard, so make sure you view lectures completely and comprehensively before attempting quizzes).

This course is oriented towards learners with similar backgrounds as juniors and seniors in a CS undergraduate curriculum. Since learners come from various backgrounds, it is critical you view this lecture AND pass the prerequisite test. This will ensure you have many of the assumed prerequisite pieces of knowledge required to enjoy this course.

Lesson 1: This module teaches how the multicast problem is solved by using epidemic/gossip protocols. It also teaches analysis of such protocols. Lesson 2: This module covers the design of failure detectors, a key component in any distributed system. Membership protocols, which use failure detectors as components, are also covered. Lesson 3: This module covers Grid computing, an important precursor to cloud computing.

P2P systems: This module teaches the detailed design of two classes of peer to peer systems: (a) popular ones including Napster, Gnutella, FastTrack, and BitTorrent; and (b) efficient ones including distributed hash tables (Chord, Pastry, and Kelips). Besides focusing on design, the module also analyzes these systems in detail.

Lesson 1: This module motivates and teaches the design of key-value/NoSQL storage/database systems. We cover the design of two major industry systems: Apache Cassandra and HBase. We also cover the famous CAP theorem. Lesson 2: Distributed systems are asynchronous, which makes clocks at different machines hard to synchronize. This module first covers various clock synchronization algorithms, and then covers ways of tagging events with causal timestamps that avoid synchronizing clocks. These classical algorithms were invented decades ago, yet are used widely in today’s cloud systems.

Lesson 1: This module covers how to calculate a distributed snapshot, leveraging causality again to circumvent the synchronization problem. Lesson 2: This lecture teaches how to order multicasts in any distributed system. Algorithms for assigning timestamp tags to multicasts using various flavors of ordering – FIFO, Causal, and Total – are covered. The module also covers virtual synchrony, a paradigm that combines reliable multicasts with membership views. Lesson 3: Consensus is one of the most important problems in a distributed system, enabling multiple machines to agree. This module uses Paxos, one of the most popular consensus solutions used in the industry today. Paxos is not perfect because consensus cannot be solved completely – an optional lecture presents the famous FLP proof of impossibility of consensus.

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.

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Ratings and Reviews

Rated 4.5 out of 5 of 473 ratings

AQ

An excellent course to start with Cloud Computing

WK

This is a great course with a good balance of just theory and concepts, with practical ideas and exercises. The programming exercise can be a bit annoying, but was enjoyable nonetheless.

VA

The course was quite enjoyable, I love the assignment part I wish it was in Java. Struggled with the C++ memory manipulation part of the algorithm which was nothing to do with the actual implementation, having not coded in C++ over a decade was reason for the struggle. Overall all quizzes and final assignment was both challenging and enjoyable.

The course provided a good overview on various topics at sufficient depth. The assignments and quizzes were challenging enough allowing one to understand the concepts in good detail.